Nausea, bloating, post-prandial fullness, early satiety, increased eructus, bowel irregularity, abdominal pain, and vomiting are symptoms that may be characteristic of a number of different diseases, which affect the stomach and upper or lower gastrointestinal tract. The symptoms may be mild, or may develop into chronic, severe, or even debilitating conditions, which adversely affect the physical and/or mental well being of an individual. The gastroenterologist, internist, or family physician that is evaluating the patient with these symptoms has many difference diseases to consider. The patients may become difficult to manage, especially when standard tests such as barium studies, ultrasound, CAT scan, MRI, and endoscopy are normal, and trials of empiric therapy fail.
Electrogastrograms (EGG) have been employed in the past to diagnose stomach disorders. These devices have been able to collect myoelectrical impulses, and accurately identify spurious signals, which have allowed manual interpretation of signals to assist in the diagnosis of gastrointestinal motility disorders. Current devices have been successful in filtering out spurious signals such as electrocardiographic electrical activity. However, some artifactual signals, such as respiratory signals, occur in frequency ranges of interest. Typically the interpretation of these signals requires manual interpretation and considerable expertise to insure accuracy and uniformity of diagnosis and accuracy of potential treatment. Even once artifact has been excluded, signal interpretation if often variable and based upon the expertise or lack thereof of the end user. Other factors such as the proper functioning of the device and acquisition of the myoelectrical signal may lead to erroneous signal recording and inaccurate subsequent interpretation and diagnosis. Even when signal is accurately acquired, and artifact is eliminated or recognized, experiential factors lead to variability in interpretation and diagnosis.
Recent research conducted with the standard electrogastrogram (EGG), has resulted in the ability to distinguish unique patterns to better diagnose various specific gastric motility disorders, including: 1) gastroesophageal reflux disease, 2) gastric outlet obstruction, and 3) pure gastric rhythm disturbances. In addition, it has been possible to further document resolution or improvement of these conditions following appropriate corrective treatment using the same device platform.
However, the current device platform requires manual post-procedural review and analysis of the signal to determine that the signal was recorded accurately to allow for subsequent manual selection of signal components for interpretation, and to arrive at a diagnostic conclusion, which must then be manually recorded.
Accordingly, there is a need to provide a novel method and system to gather and evaluate myoelectrical signals from intrabdominal and other intra-cavitary, motility based organs, such as the stomach, that will aid in the diagnosis of disorders and identify when said disorders may have been corrected, which is based upon the acquisition of the nascent signals and identification of spurious signals, but also provide for: 1) real-time analysis to allow recognition and correction of faulty signals or processes intra-procedurally, 2) intelligent auto-selection of signal components to be interpreted, 3) auto-interpretation of signals, 4) auto-diagnosis of results, and 5) instant automatic results reporting. Since the system and method are not limited to the stomach, the term “electroviscerogram” (EVG) is used herein.